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Implementation of IFPTML computational Models in Drug Discovery Against Flaviviridae Family

JOURNAL OF CHEMICAL INFORMATION AND modeling 2024年第6期64卷 1841-1852页

作者： Velasquez-Lopez, Yendrek Ruiz-Escudero, Andrea Arrasate, Sonia Gonzalez-Diaz, Humberto Univ Pais Vasco Euskal Herriko Unibertsitatea UPV Fac Ciencia & Tecnol Dept Quim Organ & Inorgan Bilbao 48080 Spain Univ Las Amer Biocheminformat Res Grp Quito 170504 Ecuador Univ Basque Country UPV EHU Dept Pharmacol Leioa 48940 Spain Univ Basque Country UPV EHU ZITEK IKERDATA SL Leioa 48940 Spain CSIC UPV EHU BIOFISIKA Basque Ctr Biophys Bilbao 48940 Spain Basque Fdn Sci IKERBASQUE Bilbao 48011 Spain

The Flaviviridae family consists of single-stranded positive-sense RNA viruses, which contains the genera Flavivirus, Hepacivirus, Pegivirus, and Pestivirus. Currently, there is an outbreak of viral diseases caused by this family affecting millions of people worldwide, leading to significant morbidity and mortality rates. Advances in computational chemistry have greatly facilitated the discovery of novel drugs and treatments for diseases associated with this family. Chemoinformatic techniques, such as the perturbation theory machine learning method, have played a crucial role in developing new approaches based on ML models that can effectively aid drug discovery. The IFPTML models have shown its capability to handle, classify, and process large data sets with high specificity. The results obtained from different models indicates that this methodology is proficient in processing the data, resulting in a reduction of the false positive rate by 4.25%, along with an accuracy of 83% and reliability of 92%. These values suggest that the model can serve as a computational tool in assisting drug discovery efforts and the development of new treatments against Flaviviridae family diseases.

关键词： Assays Chemical specificity computational modeling Drug discovery Mathematical methods

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modeling and Path Generation Approaches for Crowd Simulation Based on computational Intelligence

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Chinese Journal of Electronics 2023年第4期21卷 636-641页

作者： Hong LIU Yuling SUN Yuanyuan LI School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China

modeling and simulating group behaviours have been an active research topic in the field of computer animation and game. This paper presents some novel approaches for supporting entity modeling and path generation in crowd simulation. It analyses related work about crowd simulation first. Then, an entity modeling approach based on CGA (Cellular genetic algorithm) and NURBS (Non uniform relational B splines) technologies is presented. Next, following the analysis to PSO (Particle swarm optimization) and ABC (Artificial bee colony) algorithms, a crowd path generative approach based on ABC- PSO is put forward. After that, a simulating example of crowd cohesion and performance comparison are exhibited for showing the efficiency of the algorithms. Finally, the current work is summarized and an outlook for the future work is given.

关键词： Surface reconstruction computational modeling Sociology Animation Classification algorithms Surface topography Splines (mathematics)

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An experimental and computational investigation of executive functions and inner speech in schizophrenia spectrum disorders

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SCIENTIFIC REPORTS 2025年第1期15卷 1-21页

作者： Granato, Giovanni Costanzo, Raffaele Borghi, Anna Mattera, Andrea Carruthers, Sean Rossell, Susan Baldassarre, Gianluca Natl Res Council Italy Inst Cognit Sci & Technol Lab Embodied Nat & Artificial Intelligence Rome Italy Foro Ital Univ Rome Dept Movement Human & Hlth Sci Rome Italy Sapienza Univ Rome Dept Dynam & Clin Psychol & Hlth Studies Rome Italy Swinburne Univ Fac Hlth Arts & Design Ctr Mental Hlth & Brain Sci Sch Hlth Sci Melbourne Australia

Flexible goal-directed human cognition is supported by many forms of self-directed manipulation of representations. Among them, Inner-Speech (IS;covert self-directed speech) acts on second-order representations (e.g., goals/sub-goals), empowering attention and feedback processing. Interestingly, patients with Schizophrenia Spectrum Disorders (SSD) show impaired Executive Functions (EF;e.g., cognitive flexibility) and, probably, a related IS alteration. However, fragmentary evidence and no computational modeling prevent a clear assessment of these processes and focused therapeutic interventions. Here, we address these issues by exploiting a translational approach that integrates experimental clinical data, machine learning, and computational modeling. First, we administered the Wisconsin Cards Sorting Test (WCST;a neuropsychological test probing cognitive flexibility) to 162 SSD patients and 108 healthy control participants, and we computed the clinical behavioural data with a data-driven clustering algorithm. Second, we extracted the cluster neuropsychological profiles with our theory-based validated computational model of the WCST. Finally, we exploited our model to emulate an IS-based psychotherapeutic intervention for SSD subpopulations. We identified different SSD sub-populations and global trends (e.g., a descending feedback sensitivity);however, extremely different neuropsychological profiles emerged. In particular, 'Relatively Intact' patients showed an unexpected profile (distraction/reasoning failures), quite divergent from the perseverative/rigid profile of the others. Importantly, the former showed no impact of Interfering-IS, while the others showed increased Interfering-IS strongly affecting their cognition. These differences highlight that SSD populations require a cluster-dependent individualisation of the intervention to achieve adequate cognitive performance. Overall, these results support a clear definition of neuropsychological profiles and the re

关键词： Executive functions Inner-speech Schizophrenia spectrum disorders computational modeling

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Cellular automaton coupled with a nutrient diffusion model: a hybrid computational approach for exploring breast cancer dynamics

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INTERNATIONAL JOURNAL OF DYNAMICS AND CONTROL 2025年第4期13卷 1-23页

作者： Valentim, Carlos A. Mariuci, Giovanna David, Sergio A. Univ Sao Paulo Dept Biosyst Engn 255 Duque Caxias Norte BR-13635900 Sao Paulo Brazil Pontifical Catholic Univ Campinas Sch Med 1516 Prof Doutor Euryclides de Jesus Zerbini BR-13087571 Campinas SP Brazil

Mathematical Oncology has become a pivotal field employing both continuous and discrete models to elucidate cancer-related phenomena mathematically. When addressing physics-based models, these methods typically take the form of differential equations. However, the specific cellular structure and probabilistic behavior of tumors, especially with complex dynamics, necessitate tailor-made approaches. Cell-based models facilitate the monitoring of parameters that may fluctuate across both time and spatial dimensions, often being able to describe the fractal nature of living organisms for more realistic simulations. Building upon existing tumor growth models, our study presents cellular automata simulation techniques to virtualize breast cancer scenarios that accommodate a diverse cell population and capture the patterns of both individual cells and cell clusters. In conjunction with this stochastic approach, we have integrated a model using partial differential equations to simulate nutrient diffusion within the tumor microenvironment, offering insights into complex biosystem dynamics. Our findings indicate that parameter adjustments, especially in the subparameters of the probability modulator, significantly impact the simulated tumor's growth, apoptosis, and migration patterns. The proposed hybrid cellular automaton model is capable of simulating varying tumor growth scenarios, positioning it as a valuable multivariate dynamics tool for in silico experimentation. Moreover, this model lays the groundwork for further integration with data-driven techniques capable of analyzing clinical data and diagnostic imagery. This anticipated framework, which incorporates fractal and fractional modeling concepts, calls for interdisciplinary collaboration to merge diverse resources and methodologies into innovative concepts in oncology, contributing to the prospective refinement of diagnostic tools and treatment modalities.

关键词： Mathematical oncology Tumor growth In-silico experimentation computational modeling Hybrid models

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Dry ice sublimation: A computational study with experimental validation for the effects of geometry

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JOURNAL OF FOOD SCIENCE 2025年第1期90卷 e17496页

作者： Erdogdu, Ferruh Hafner, Kimberly Altin, Ozan Karatas, Ozan Boz, Ziynet Welt, Bruce A. Ankara Univ Dept Food Engn Ankara Turkiye Univ Florida Dept Agr & Biol Engn Gainesville FL 32611 USA Ankara Univ Grad Sch Nat & Appl Sci Dept Food Engn Ankara Turkiye

Dry ice is one of the world's most in-demand commodities for cold-chain distribution of temperature-sensitive products. It offers an effective cooling solution without requiring mechanical refrigeration or specialized equipment. Dry ice is commonly produced as pellets and blocks. A widely used "rule of thumb" suggests that dry ice sublimates about 3%-8% per day. Mass of dry ice is typically the only packaging specification and/or regulatory limitation, even though sublimation rate is highly dependent on geometry. Therefore, the purpose of this study was to develop and validate a computational model for the sublimation process and to elucidate effects of geometry and orientation on dry ice sublimation. Experiments on sublimation of dry ice blocks were carried out and used to validate a multi-physics model involving radiation and convection heat transfer, computational fluid dynamics, and changes in the geometrical features. Following model validation, effects of dry ice geometry on sublimation rates were evaluated. Volume-to-surface area ratio was found to be a significant sublimation cooling performance parameter. Results showed that for the same mass, the rate of sublimation in the form of a sphere (high volume-to-surface area ratio) was almost half that of dry ice in the form of a block (lower volume-to-surface area ratio). This finding enhances our understanding of dry ice sublimation and cooling, which promises to help to improve practical cold-chain maintenance.

关键词： cold chain computational modeling dry ice geometry sublimation

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A review of computational optimization of bone scaffold architecture: methods, challenges, and perspectives

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PROGRESS IN BIOMEDICAL ENGINEERING 2025年第1期7卷 012003-012003页

作者： Foroughi, Ali H. Valeri, Caleb Razavi, Mir Jalil SUNY Binghamton Dept Mech Engn Binghamton NY 13902 USA

The design and optimization of bone scaffolds are critical for the success of bone tissue engineering (BTE) applications. This review paper provides a comprehensive analysis of computational optimization methods for bone scaffold architecture, focusing on the balance between mechanical stability, biological compatibility, and manufacturability. Finite element method (FEM), computational fluid dynamics (CFD), and various optimization algorithms are discussed for their roles in simulating and refining scaffold designs. The integration of multiobjective optimization and topology optimization has been highlighted for developing scaffolds that meet the multifaceted requirements of BTE. Challenges such as the need for consideration of manufacturing constraints and the incorporation of degradation and bone regeneration models into the optimization process have been identified. The review underscores the potential of advanced computational tools and additive manufacturing techniques in evolving the field of BTE, aiming to improve patient outcomes in bone tissue regeneration. The reliability of current optimization methods is examined, with suggestions for incorporating non-deterministic approaches and in vivo validations to enhance the practical application of optimized scaffolds. The review concludes with a call for further research into artificial intelligence-based methods to advance scaffold design and optimization.

关键词： computational modeling internal architecture finite element method computational fluid dynamics optimization bone scaffold

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Benchmarking and Reproducibility in computational and Experimental Characterization of Electronic Packages for Signal/Power Integrity: Four benchmarks serve as standardized cases

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IEEE ANTENNAS AND PROPAGATION MAGAZINE 2025年第2期67卷 51-63页

作者： Barnes, Heidi Aygun, Kemal Hill, Michael J. Zhang, Zhichao Hu, Kaisheng Aronsson, Jonatan Paladhi, Pavel Balachandran, Jayaprakash Shi, Bobi Sharma, Rohit Schutt-Aine, Jose E. Okhmatovski, Vladimir I. EEsof EDA Grp Keysight Technol Santa Rosa CA 95403 USA Intel Corp Chandler AZ 85226 USA Ciena Ottawa ON K2K 3L2 Canada CEMWorks Winnipeg MB R3P 0E1 Canada Nvidia San Jose CA 95134 USA D Matrix Inc Santa Clara CA 95054 USA Google Mountain View CA 94043 USA Penn State Univ Sch EECS University Pk PA 16802 USA Univ Illinois Elect & Comp Engn Dept Urbana IL 61801 USA Univ Manitoba Dept Elect & Comp Engn Winnipeg MB R3T 5V6 Canada

This article describes current initiatives to form benchmarks for the characterization of electronic packages. Four available benchmarks representing typical cases for signal integrity (SI) and power integrity (PI) analysis and varying in complexity from simple microstrip line to a full package model are intended to serve as standardized cases for testing the performance and accuracy of the modeling tools. While the benchmarks, consisting of CAD model files as well as simulated and measured network parameters, are publicly available and described in the accompanying manual, the emphasis in this article is on the description of challenges encountered in creating measured data, the development of modeling capabilities in the computational tools essential for accurate and expedient electromagnetic (EM) analysis of the benchmarks, and common practices going into matching of the simulated to the measured data. Ongoing efforts toward the standardization of densely packed interconnects for die-to-die interfacing on advanced packages, also known as heterogeneous integration (HI), are discussed in the context of the Open Compute Project (OCP). Emerging needs for benchmarking and standardization of test cases and training datasets for machine learning (ML)-assisted characterization of high-speed channels are also outlined.

关键词： Antenna measurements Training Solid modeling Analytical models Accuracy computational modeling Benchmark testing Data models Reproducibility of results Signal integrity

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Guest Editorial Special Issue on Resource Sustainable computational and Artificial Intelligence

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IEEE TRANSACTIONS ON EMERGING TOPICS IN computational INTELLIGENCE 2024年第5期8卷 3196-3198页

作者： Zhou, Joey Tianyi Tsang, Ivor W. Ong, Yew Soon ASTAR Singapore 138632 Singapore Nanyang Technol Univ Singapore 639798 Singapore

In Recent years, the rapid advancements in computational and artificial intelligence (C/AI) have led to successful applications across various disciplines, driven by neural networks and powerful computing hardware. However, these achievements come with a significant challenge: the resource-intensive nature of current AI systems, particularly deep learning models, results in substantial energy consumption and carbon emissions throughout their lifecycle. This resource demand underscores the urgent need to develop resource-constrained AI and computational intelligence methods. Sustainable C/AI approaches are crucial not only to mitigate the environmental impact of AI systems but also to enhance their role as tools for promoting sustainability in industries like reliability engineering, material design, and manufacturing.

关键词： Special issues and sections Artificial intelligence Sustainable development computational modeling Object recognition Sensors Image reconstruction Internet of Things Deep learning Computer architecture Neural networks Resource management Environmental factors Energy consumption Carbon emissions Reliability engineering

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Improving computational models of deep brain stimulation through experimental calibration

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JOURNAL OF NEUROSCIENCE METHODS 2025年 414卷 110320页

作者： Payonk, Jan Philipp Bathel, Henning Arbeiter, Nils Kober, Maria Fauser, Mareike Storch, Alexander van Rienen, Ursula Zimmermann, Julius Univ Rostock Inst Gen Elect Engn Albert Einstein Str 2 D-18051 Rostock Germany Univ Rostock Dept Neurol Gehlsheimer Str 20 D-18147 Rostock Germany German Ctr Neurodegenerat Dis DZNE Rostock Greifsw Gehlsheimer Str 20 D-18147 Rostock Germany Univ Rostock Dept Life Light & Matter Albert Einstein Str 25 D-18051 Rostock Germany Univ Rostock Dept Ageing Individuals & Soc Albert Einstein Str 21 D-18051 Rostock Germany Univ Pavia Dept Civil Engn & Architecture Synthet Physiol Lab Pavia Italy

Background: Deep brain stimulation has become a well-established clinical tool to treat movement disorders. Nevertheless, the knowledge of processes initiated by the stimulation remains limited. To address this knowledge gap, computational models are developed to gain deeper insight. However, their predictive power remains constrained by model uncertainties and a lack of validation and calibration. New method: Exemplified with rodent microelectrodes, we present a workflow for validating electrode model geometry using microscopy and impedance spectroscopy in vitro before implantation. We address uncertainties in the tissue distribution and dielectric properties and outline a concept for calibrating the computational model based on in vivo impedance spectroscopy measurements. Results: The standard deviation of the volume of tissue activated across the 18 characterized electrodes was approximately 32.93%, underscoring the importance of electrode characterization. Thus, the workflow significantly enhances the model predictions' credibility of neural activation exemplified in a rodent model. Comparison with existing methods: computational models are frequently employed without validation or calibration, relying instead on manufacturers' specifications. Our approach provides an accessible method to obtain a validated and calibrated electrode geometry, which significantly enhances the reliability of the computational model that relies on this electrode. Conclusion: By reducing the uncertainties of the model, the accuracy in predicting neural activation is increased. The entire workflow is realized in open-source software, making it adaptable for other use cases, such as deep brain stimulation in humans. Additionally, the framework allows for the integration of further experiments, enabling live updates and refinements to computational models.

关键词： computational modeling Deep brain stimulation Impedance spectroscopy Encapsulation tissue Dielectric properties Uncertainty quantification

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How to be a realist about computational neuroscience

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SYNTHESE 2025年第3期205卷 1-27页

作者： Williams, Danielle J. Washington Univ St Louis St Louis MO 63130 USA

Recently, a version of realism has been offered to address the simplification strategies used in computational neuroscience. According to this view, computational models provide us with knowledge about the brain, but they should not be taken literally in any sense, even rejecting the idea that the brain performs computations (computationalism). I acknowledge the need for considerations regarding simplification strategies in neuroscience and how they contribute to our interpretations of computational models;however, I argue that whether we should accept or reject computationalism about the brain is a separate issue that can be addressed independently by a philosophical theory of physical computation. This takes seriously the idea that the brain performs computations while also taking an analogical stance toward computational models in neuroscience. I call this version of realism "Analogical computational Realism." Analogical computational Realism is a realist view in virtue of being committed to computationalism while taking certain computational models to pick out real patterns that provide a how-possibly explanation without also thinking that the model is literally implemented in the brain.

关键词： Realism Idealization computational modeling Neuroscience

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